Our CEO, Dr. Michael Haft, is featured in Issue #13 of Data & AI Magazine on “Understanding Cause and Effect: Is Causal Discovery the Missing Layer in Artificial Intelligence?”
While generative AI continues to dominate the conversation, Causal AI focuses on a different question: not just what will happen, but why it happens. Understanding cause-and-effect relationships is essential for building AI systems that are explainable, reliable, and capable of supporting better decisions.
In the interview, Michael discusses how Causal Discovery helps distinguish true causal relationships from simple correlations and why this capability will become increasingly important as AI moves from prediction to intelligent intervention.
We’re pleased to be part of this discussion and would like to thank Damien Deighan and the entire Data & AI Magazine team for the opportunity to contribute.
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Read the full interview with Dr. Michael Haft.
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